1. Cybersecurity on Telehealth @NIST
2. Cybersecurity on Telehealth x Smart Home @NIST
3. Cloud-Native Privacy/Data Protection on Telehealth @CSA
4. Cloud-Native Security on Telehealth @CSA
5. Conclusions
IoT security and privacy: main challenges and how ISOC-OTA address themRadouane Mrabet
Internet Society (ISOC) aims are:
make security an integrated function of connected objects and encourages IoT device and service providers for consumers to adopt the Online Trust Alliance (OTA) security and privacy principles ;
increase the consumer demand for security and privacy in the IoT devices they purchase;
create government policies and regulations that promote better security and privacy features in IoT devices.
Cloud computing is rapidly evolving due to its efficient characteristics such as cost-effectiveness,
availability and elasticity. Healthcare organizations and consumers lose control when they outsource their
sensitive data and computing resources to a third party Cloud Service Provider (CSP), which may raise
security and privacy concerns related to data loss and misuse appealing threats. Lack of consumers’
knowledge about their data storage location may lead to violating rules and regulations of Health Insurance
Portability and Accountability Act (HIPAA) that can cost them huge penalty. Fear of data breach by internal
or external hackers may decrease consumers’ trust in adopting cloud computing and benefiting from its
promising features. We designed a HealthcareTrusted Cloud Computing (HTCC) framework that maintains
security, privacy and considers HIPAA regulations. HTCC framework deploys Trusted Computing Group
(TCG) technologies such as Trusted Platform Module (TPM), Trusted Software Stack (TSS), virtual
Trusted Platform Module (vTPM), Trusted Network Connect (TNC) and Self Encrypting Drives (SEDs).
We emphasize on using strong multi-factor authentication access control mechanisms and strict security
controls, as well as encryption for data at storage, in-transit and while process. We contributed in
customizing a cloud Service Level Agreement (SLA) by considering healthcare requirements. HTCC was
evaluated by comparing with previous researchers’ work and conducting survey from experts. Results were
satisfactory and showed acceptance of the framework. We aim that our proposed framework will assist in
optimizing trust on cloud computing to be adopted in healthcare sector.
A Novel Healthcare-based Block chain (HBC) System for Security Healthcare Dat...IRJET Journal
The document proposes a novel healthcare blockchain (HBC) system to securely store patient healthcare data and protect patient privacy. The HBC would address issues related to securing patient data by storing encrypted data on off-chain storage and the hash of the encrypted data on the blockchain. This ensures patient data is private while maintaining integrity and traceability on the blockchain. The system would also implement fine-grained access control where patients own their data and can grant different permission levels to healthcare providers. This allows patients transparency and auditability over who accesses their healthcare information.
In the last few years, cloud computing has grown from being a promising business concept to one of the fastest growing segments of the IT industry. Now, recession-hit companies are increasingly realizing that simply by tapping into the cloud they can gain fast access to best-of-breed business applications or drastically boost their infrastructure resources, all at negligible cost. But as more and more information on individuals and companies is placed in the cloud, concerns are beginning to grow about just how safe an environment it is. This paper discusses security issues, requirements and challenges that cloud service providers (CSP) face during cloud engineering. Recommended security standards and management models to address these are suggested for technical and business community.
Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
The document discusses using deep learning and big data technologies to improve security for Internet of Things (IoT) devices and networks. Specifically, it proposes using deep learning models to analyze large amounts of data from IoT sensors to better detect and classify security threats. This can help identify attacks like botnets and distributed denial-of-service (DDoS) attacks. The document also outlines some common IoT security challenges and how approaches like Apache Hadoop, Spark, and Storm can process large volumes of IoT data to improve real-time monitoring and threat prevention.
IRJET- Comprehensive Study of E-Health Security in Cloud ComputingIRJET Journal
This document discusses security challenges with storing electronic health records (EHRs) in cloud computing environments. It begins with an abstract that outlines how cloud computing enables easy sharing of EHRs but also raises security and privacy concerns since records are stored with third-party cloud providers. The document then reviews literature on securing EHR data in the cloud and categorizes approaches as cryptographic (using encryption) or non-cryptographic. It identifies that current encryption methods are inefficient and do not prevent insider threats from key administrators. The document proposes a new framework supported by blockchain technology to address weaknesses while ensuring privacy and security of EHRs stored in the cloud.
IRJET - Healthcare Data Storage using BlockchainIRJET Journal
This document discusses using blockchain technology for healthcare data storage. It begins by introducing blockchain and how it can improve data security, transparency and access for healthcare applications. It then reviews related work applying blockchain to healthcare, medical records, clinical trials and more. The document proposes a system using blockchain to securely store healthcare data records and transactions. The system would create patient accounts, allow medical reports to be submitted, generate transactions, add blocks of transactions to the blockchain, and enable validation of insurance claims. In conclusion, the document discusses how blockchain can efficiently scale to handle large healthcare data volumes and users while facilitating easier interoperability between systems.
DIFFERENCES OF CLOUD-BASED SERVICES AND THEIR SAFETY RENEWAL IN THE HEALTH CA...IRJET Journal
The document discusses the benefits and risks of cloud-based services for the healthcare system. It begins by introducing how cloud computing has impacted various sectors including healthcare by enabling storage of large amounts of patient data and easy access. It then categorizes existing cloud applications and services used in healthcare. The document also analyzes security and privacy risks of cloud-based healthcare services and compares the risks of secure vs insecure cloud systems. It proposes that adopting cloud services in healthcare requires addressing security issues.
IoT security and privacy: main challenges and how ISOC-OTA address themRadouane Mrabet
Internet Society (ISOC) aims are:
make security an integrated function of connected objects and encourages IoT device and service providers for consumers to adopt the Online Trust Alliance (OTA) security and privacy principles ;
increase the consumer demand for security and privacy in the IoT devices they purchase;
create government policies and regulations that promote better security and privacy features in IoT devices.
Cloud computing is rapidly evolving due to its efficient characteristics such as cost-effectiveness,
availability and elasticity. Healthcare organizations and consumers lose control when they outsource their
sensitive data and computing resources to a third party Cloud Service Provider (CSP), which may raise
security and privacy concerns related to data loss and misuse appealing threats. Lack of consumers’
knowledge about their data storage location may lead to violating rules and regulations of Health Insurance
Portability and Accountability Act (HIPAA) that can cost them huge penalty. Fear of data breach by internal
or external hackers may decrease consumers’ trust in adopting cloud computing and benefiting from its
promising features. We designed a HealthcareTrusted Cloud Computing (HTCC) framework that maintains
security, privacy and considers HIPAA regulations. HTCC framework deploys Trusted Computing Group
(TCG) technologies such as Trusted Platform Module (TPM), Trusted Software Stack (TSS), virtual
Trusted Platform Module (vTPM), Trusted Network Connect (TNC) and Self Encrypting Drives (SEDs).
We emphasize on using strong multi-factor authentication access control mechanisms and strict security
controls, as well as encryption for data at storage, in-transit and while process. We contributed in
customizing a cloud Service Level Agreement (SLA) by considering healthcare requirements. HTCC was
evaluated by comparing with previous researchers’ work and conducting survey from experts. Results were
satisfactory and showed acceptance of the framework. We aim that our proposed framework will assist in
optimizing trust on cloud computing to be adopted in healthcare sector.
A Novel Healthcare-based Block chain (HBC) System for Security Healthcare Dat...IRJET Journal
The document proposes a novel healthcare blockchain (HBC) system to securely store patient healthcare data and protect patient privacy. The HBC would address issues related to securing patient data by storing encrypted data on off-chain storage and the hash of the encrypted data on the blockchain. This ensures patient data is private while maintaining integrity and traceability on the blockchain. The system would also implement fine-grained access control where patients own their data and can grant different permission levels to healthcare providers. This allows patients transparency and auditability over who accesses their healthcare information.
In the last few years, cloud computing has grown from being a promising business concept to one of the fastest growing segments of the IT industry. Now, recession-hit companies are increasingly realizing that simply by tapping into the cloud they can gain fast access to best-of-breed business applications or drastically boost their infrastructure resources, all at negligible cost. But as more and more information on individuals and companies is placed in the cloud, concerns are beginning to grow about just how safe an environment it is. This paper discusses security issues, requirements and challenges that cloud service providers (CSP) face during cloud engineering. Recommended security standards and management models to address these are suggested for technical and business community.
Deep Learning and Big Data technologies for IoT SecurityIRJET Journal
The document discusses using deep learning and big data technologies to improve security for Internet of Things (IoT) devices and networks. Specifically, it proposes using deep learning models to analyze large amounts of data from IoT sensors to better detect and classify security threats. This can help identify attacks like botnets and distributed denial-of-service (DDoS) attacks. The document also outlines some common IoT security challenges and how approaches like Apache Hadoop, Spark, and Storm can process large volumes of IoT data to improve real-time monitoring and threat prevention.
IRJET- Comprehensive Study of E-Health Security in Cloud ComputingIRJET Journal
This document discusses security challenges with storing electronic health records (EHRs) in cloud computing environments. It begins with an abstract that outlines how cloud computing enables easy sharing of EHRs but also raises security and privacy concerns since records are stored with third-party cloud providers. The document then reviews literature on securing EHR data in the cloud and categorizes approaches as cryptographic (using encryption) or non-cryptographic. It identifies that current encryption methods are inefficient and do not prevent insider threats from key administrators. The document proposes a new framework supported by blockchain technology to address weaknesses while ensuring privacy and security of EHRs stored in the cloud.
IRJET - Healthcare Data Storage using BlockchainIRJET Journal
This document discusses using blockchain technology for healthcare data storage. It begins by introducing blockchain and how it can improve data security, transparency and access for healthcare applications. It then reviews related work applying blockchain to healthcare, medical records, clinical trials and more. The document proposes a system using blockchain to securely store healthcare data records and transactions. The system would create patient accounts, allow medical reports to be submitted, generate transactions, add blocks of transactions to the blockchain, and enable validation of insurance claims. In conclusion, the document discusses how blockchain can efficiently scale to handle large healthcare data volumes and users while facilitating easier interoperability between systems.
DIFFERENCES OF CLOUD-BASED SERVICES AND THEIR SAFETY RENEWAL IN THE HEALTH CA...IRJET Journal
The document discusses the benefits and risks of cloud-based services for the healthcare system. It begins by introducing how cloud computing has impacted various sectors including healthcare by enabling storage of large amounts of patient data and easy access. It then categorizes existing cloud applications and services used in healthcare. The document also analyzes security and privacy risks of cloud-based healthcare services and compares the risks of secure vs insecure cloud systems. It proposes that adopting cloud services in healthcare requires addressing security issues.
DIFFERENCES OF CLOUD-BASED SERVICES AND THEIR SAFETY RENEWAL IN THE HEALTH CA...IRJET Journal
The document discusses the benefits and risks of cloud-based services for healthcare systems. It begins by outlining how cloud computing has enabled new diagnostic technologies and easy access to patient data. However, it also notes security and privacy risks, such as data breaches and unauthorized access. The document then reviews existing literature on revolutionary impacts of cloud solutions, predictive threat analysis using big data, and risk analysis of cloud models. It proposes a methodology for categorizing cloud benefits and risks to help healthcare workers and IT professionals. The methodology aims to securely manage data exchange while addressing challenges like cyberattacks and lack of technical knowledge.
FEDERAL LEARNING BASED SOLUTIONS FOR PRIVACY AND ANONYMITY IN INTERNET OF MED...IRJET Journal
This document discusses the use of federated learning (FL) for privacy-preserving analysis of medical data from internet of things (IoT) devices. FL allows decentralized training of machine learning models on devices without moving sensitive patient data to a central location. The rise of IoT in healthcare is generating huge volumes of data but current AI approaches require aggregating data, raising privacy and security concerns. FL emerges as a solution by enabling decentralized and collaborative training while keeping data on devices. The document reviews literature on applying FL to clinical IoT applications and discusses how FL can address data isolation issues and perform AI tasks without compromising privacy.
IRJET- Secrecy Preserving and Intrusion Avoidance in Medical Data Sharing...IRJET Journal
This document summarizes a research paper that proposes a cloud-based healthcare system for securely sharing medical data. It does the following:
1. It encrypts patient medical data using the NTRU encryption algorithm when transmitting it to nearby clouds for privacy.
2. It develops a trust model to help users select trustworthy partners to share stored medical data with in the cloud based on their similarity and compatibility.
3. It divides and encrypts users' medical data stored in the remote cloud into different categories to provide appropriate security protections.
4. It implements a deliberative intrusion detection system based on the cloud mesh structure to safeguard the large medical database in the remote cloud from malicious attacks.
USING BLOCKCHAIN TO ACHIEVE DECENTRALIZED PRIVACY IN IOT HEALTHCAREIJCI JOURNAL
With the advent of the Internet of Things (IoT), e-health has become one of the main topics of research. Due to the sensitivity of patient information, patient privacy seems challenging. Nowadays, patient data is usually stored in the cloud in healthcare programs, making it difficult for users to have enough control over their data. The recent increment in announced cases of security and surveillance breaches compromising patients' privacy call into question the conventional model, in which third-parties gather and control immense amounts of patients' Healthcare data. In this work, we try to resolve the issues mentioned above by using blockchain technology. We propose a blockchain-based protocol suitable for ehealth applications that does not require trust in a third party and provides an efficient privacy-preserving access control mechanism. Transactions in our proposed system, unlike Bitcoin, are not entirely financial, and we do not use conventional methods for consensus operations in blockchain like Proof of Work (PoW). It is not suitable for IoT applications because IoT devices have resources-constraints. Usage of appropriate consensus method helps us to increase network security and efficiency, as well as reducing network cost, i.e., bandwidth and processor usage. Finally, we provide security and privacy analysis of our proposed protocol.
This document proposes an e-health cloud solution to securely store patient health records and reports in the cloud. Previously, patient documents were stored physically taking up space and making it difficult to access old records. The cloud solution aims to address these issues by digitizing records and storing them securely in the cloud. This allows easy access to records from anywhere and saves space. The document discusses challenges with healthcare cloud computing like data security and privacy. It proposes using encryption and multi-factor authentication for cloud data and user access security.
IRJET- Implementation of Cloudlet-based Medical Data Sharing using ECC Crypto...IRJET Journal
This document proposes a cloudlet-based medical data sharing framework that uses encryption to securely share patient data. It discusses encrypting medical data with ECC cryptography before storing it on a cloudlet. A collaborative intrusion detection system is also developed to protect the remote healthcare cloud from attacks. The framework allows trusted partners like doctors to access encrypted data from the cloudlet after being authenticated. It aims to securely share medical data for similar patients while preserving patient privacy.
Cloud assisted privacy preserving and data integrity for mobile health monito...eSAT Journals
Abstract
In cloud computing system ,data is stimulated to a distantly placed cloud server. Cloud provisions the information authentically and go back to the proprietor whenever wanted. But there is no assurance that information store in the cloud is protected and not changed by cloud . In order to defeat the danger of honesty of data, the user must be able to use the help of Third party Auditor(TPA).TPA has understanding in inspection honesty of the information, that clouds users does not have, and that is difficult for the owner to check .The data in the cloud should be exact ,reliable ,available and elevated excellence.[1]This paper is to address this important problem related to the data integrity and design a cloud assisted privacy preserving mobile-health monitoring system to protect the privacy of the involved parties and their data. for that purpose we have used the algorithms:1)Tate pairing 2)Token generation 3)AES(Advanced Encryption Standards)-SHA1 and MD5.
Keywords— Data integrity,TPA,Tate pairing, Cryptography
Achieving Data Dissemination with Security using FIWARE and Intel Software Gu...Dalton Valadares
This document proposes and evaluates a solution to securely disseminate sensitive IoT data using FIWARE and Intel SGX. The solution uses FIWARE components for authentication and authorization, and introduces a new Key Vault component that uses Intel SGX to securely store and manage encryption keys. Sensitive IoT data from smart meters is encrypted before being sent to the FIWARE Orion Context Broker for processing. Consumers that are SGX applications can decrypt and process the data securely within the SGX enclave. The evaluation shows the solution provides privacy and security guarantees without harming scalability or availability.
Security and Privacy of Big Data in Mobile DevicesIOSRjournaljce
Presently, the volume of data generated via mobile devices is at an exponential rate due to the rapid advancement in internet-enabled mobile devices, which makes it complex to ensure the privacy and security of this data. Cloud-based server is currently considered one of the most reliable solutions to address these issues. Nevertheless, the increasing uncertainties of storing useful and sensitive big data in a public cloud have suppressed the exploration of this option. In our paper, we meticulously reviewed the drawbacks in the current adopted solutions for security and privacy of big data within mobile devices. As the utilization of mobile platforms is increasingly generating large data, the current traditional methods of cryptography will not be able to efficiently ensure the security and privacy of this big data. Therefore, this paper will propose the utilization of Federated Identity Management that is Openstack cloud-based as an effective solution that can ensure the privacy and security of big data within mobile device ecosystem.
IRJET- Secure Re-Encrypted PHR Shared to Users Efficiently in Cloud ComputingIRJET Journal
This document proposes a Securely Re-Encrypted PHR Shared to Users Efficiently in Cloud Computing (SeSPHR) system. The SeSPHR system aims to securely store and share patients' Personal Health Records (PHRs) with authorized entities in the cloud while preserving privacy. It encrypts PHRs stored on untrusted cloud servers and only allows verified users access using re-encryption keys from a semi-trusted proxy server. The system enforces patient-centric access management of PHR components based on access levels and supports dynamic addition and removal of authorized users. The operation of SeSPHR was analyzed and verified using High-Level Petri Nets, SMT-Lib and Z3 solver. Performance analysis
This document discusses strategies for ensuring the security of enterprise image viewers and mobile health solutions. It notes that data security is a major concern in healthcare, with security breaches potentially resulting in large fines. The document then recommends educating staff on mobile security, using device security features, implementing network security policies, using authentication, secure connections, and ensuring solutions have built-in encryption and integrate with IT policies. It outlines Calgary Scientific's approach to securing its ResolutionMD image viewer, which does not leave patient data on devices, requires login credentials, uses SSL encryption, and optionally a VPN.
Framework to Manage Big Data in Smart Home Servicesijtsrd
In order to improve the effect of smart home control and management, a new smart home control and management method based on big data analysis is designed. The basic hardware of smart home control and management is designed, including smoke sensor hardware, temperature and humidity sensor hardware, and infrared sensor hardware, so as to collect smart home data and realize data visualization and buzzer alarm. The collected data are transmitted through the indoor wireless network of smart home gateway equipment, and the data distributed cache architecture based on big data analysis is used to store smart home data. Based on the relevant data, the hybrid particle swarm optimization algorithm is used to schedule the control and management tasks of smart home to complete the control and management of smart home. Dr. Rajendra Kumar Bharti "Framework to Manage Big Data in Smart Home Services" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52102.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/52102/framework-to-manage-big-data-in-smart-home-services/dr-rajendra-kumar-bharti
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document discusses privacy issues in cloud computing. It defines privacy and describes privacy enhancing technologies (PETs) that can help protect privacy, such as pseudonymization and federated identity management. It also discusses privacy by design, which aims to embed privacy protections directly into technologies. Ensuring privacy in cloud computing requires measures like access controls, protecting against unauthorized access/copying of data, and specifying privacy controls in agreements. Overall privacy is a major challenge for cloud computing due to issues of data governance, security, and differing international regulations.
IRJET - Health Record Transaction in Hospital Management using BlockchainIRJET Journal
This document proposes a Secure and Efficient Health Record Transaction algorithm (SEHRTB) using blockchain technology. The SEHRTB aims to securely store and transact health records between patients, doctors, hospitals, and insurance agents in a decentralized manner. It describes a system where patient health records are encrypted and stored on a distributed ledger. Only authorized parties like doctors and insurance agents can access the encrypted records after getting the necessary keys. The proposed SEHRTB algorithm is evaluated and shown to reduce latency, execution time, and improve throughput compared to existing methods. The system aims to provide privacy and security for health records transactions using blockchain.
The document discusses encryption strategies used by organizations that have experienced data breaches. While encryption is commonly used, it is often not applied or used properly, leaving entire systems vulnerable. For encryption to be effective, companies must use a comprehensive defense in depth strategy where data is encrypted and keys are protected across all systems where encrypted data needs to be accessed and managed. Target spent heavily on security but a weakness allowed cybercriminals to access encrypted data in memory before it was encrypted. Stronger defenses are needed at each layer to block attacks.
Enhancing security features in cloud computing for healthcare using cipher an...eSAT Journals
Abstract Health Care is the most important unindustrialized field. Cloud is an emerging trend in software industry. In medical field, there are large dataset comprising highly sensitive data about patient’s medical records. Based on these records, diagnosis for the patient will be given. Moving data to the cloud makes to explore a large information for diagnosis as expert documentation will also be stored as part of health record. Physicians from anywhere at any time can get access over these reports for better treatment. The Medicare industry vacillates to store these data to the cloud as the patients might feel insecure about their health records. This work introduces the idea of combining Cipher Cloud, Inter Cloud and ABE schemes, proposes an innovative method to enhance security features in the cloud by double encryption using algorithms and tools. By this, only authorized entities are proficient of accessing these records. Rather than storing data in single cloud, Inter Cloud (Multi-cloud) also adds advantage for our proposed work. Keywords: Virtualization, Cipher cloud, Trust, Encryption, Inter cloud
Enhancing security features in cloud computing for healthcare using cipher an...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
I want you to Read intensively papers and give me a summary for ever.pdfamitkhanna2070
I want you to Read intensively papers and give me a summary for every paper and the linghth for
each paper is 2 pages or more. In the summary, you need to provide some of your own ideas.
Research Interests: Privacy-Aware Computing,Wireless and Mobile Security,Fog
Computing,Mobile Health and Safety, Cognitive Radio Networking,Algorithm Design and
Analysis.
You should select papers from the following conferences:
IEEE INFOCOM, IEEE Symposium on security and privacy, ACM CCS, USENIX Security.
Solution
PRIVACY AWARE COMPUTING
Introduction
With the increasing public concerns of security and personal data privacy worldwide, security
and privacy become an important research area. This research area is very broad and covers
many application domains.
The security and privacy aware computing research group actually focuses on
(1) privacy-preserved computing,
(2) Video surveillance, and
(3) secure biometric system.
Now let us briefly discuss the above three groups.
Privacy-preserved Computing
Concerns on the data privacy have been increasing worldwide. For example, Apple was
reportedly fined by South Korea’s telecommunications regulator for allegedly collecting and
storing private location data of iPhone users. The privacy concerns raised by both end-users and
government authorities have been hindering the deployment of many valuable IT services, such
as data mining and analysis, data outsourcing, and mobile location-aware computing.
soo, in response to the growing necessity of protecting data privacy, our research group has been
focusing on developing innovative solutions towards information services --- to support these
services while preserving users’ personal privacy.
Video Surveillance
With the growing installation of surveillance video cameras in both private and public areas, the
closed-circuit TV (CCTV) has been evolved from a single camera system to a multiple camera
system; and has recently been extended to a large-scale network of cameras.
One of the objectives of a camera network is to monitor and understand security issues in the
area under surveillance. While the camera network hardware is generally well-designed and
roundly installed, the development of intelligent video analysis software lags far behind. As
such, our group has been focusing on developing video surveillance algorithms such as face
tracking, person re-identification, human action recognition.
Our goal is to develop an intelligent video surveillance system.
Secure Biometric System
With the growing use of biometrics, there is a rising concern about the security and privacy of
the biometric data. Recent studies show that simple attacks on a biometric system, such as hill
climbing, are able to recover the raw biometric data from stolen biometric template. Moreover,
the attacker may be able to make use of the stolen face template to access the system or cross-
match across databases. Our group has been working on face template protection, multimodality
template protection, and .
Healthcare information exchange using blockchain technologyIJECEIAES
This document proposes a blockchain-based healthcare information exchange system using Hyperledger Fabric. The system would allow secure sharing of electronic health records between patients, doctors, hospitals, insurance companies, and research organizations. Medical data is sensitive, so a permissioned blockchain like Hyperledger Fabric is used to control access while maintaining privacy. The system aims to provide consistent and accessible health records for patients while giving them control over access permissions. A backup access system using wearable devices would allow access to critical health information in emergencies.
1. What Is “Metaverse”?
2. Use Cases of Metaverse in Healthcare: Robot-Assisted Surgery (RAS) Systems
3. What Is “Web3/NFTs”?
4. Use Cases of Web3/NFTs in Healthcare: Secure Health Information Exchange
5. Conclusion/Q&A
DIFFERENCES OF CLOUD-BASED SERVICES AND THEIR SAFETY RENEWAL IN THE HEALTH CA...IRJET Journal
The document discusses the benefits and risks of cloud-based services for healthcare systems. It begins by outlining how cloud computing has enabled new diagnostic technologies and easy access to patient data. However, it also notes security and privacy risks, such as data breaches and unauthorized access. The document then reviews existing literature on revolutionary impacts of cloud solutions, predictive threat analysis using big data, and risk analysis of cloud models. It proposes a methodology for categorizing cloud benefits and risks to help healthcare workers and IT professionals. The methodology aims to securely manage data exchange while addressing challenges like cyberattacks and lack of technical knowledge.
FEDERAL LEARNING BASED SOLUTIONS FOR PRIVACY AND ANONYMITY IN INTERNET OF MED...IRJET Journal
This document discusses the use of federated learning (FL) for privacy-preserving analysis of medical data from internet of things (IoT) devices. FL allows decentralized training of machine learning models on devices without moving sensitive patient data to a central location. The rise of IoT in healthcare is generating huge volumes of data but current AI approaches require aggregating data, raising privacy and security concerns. FL emerges as a solution by enabling decentralized and collaborative training while keeping data on devices. The document reviews literature on applying FL to clinical IoT applications and discusses how FL can address data isolation issues and perform AI tasks without compromising privacy.
IRJET- Secrecy Preserving and Intrusion Avoidance in Medical Data Sharing...IRJET Journal
This document summarizes a research paper that proposes a cloud-based healthcare system for securely sharing medical data. It does the following:
1. It encrypts patient medical data using the NTRU encryption algorithm when transmitting it to nearby clouds for privacy.
2. It develops a trust model to help users select trustworthy partners to share stored medical data with in the cloud based on their similarity and compatibility.
3. It divides and encrypts users' medical data stored in the remote cloud into different categories to provide appropriate security protections.
4. It implements a deliberative intrusion detection system based on the cloud mesh structure to safeguard the large medical database in the remote cloud from malicious attacks.
USING BLOCKCHAIN TO ACHIEVE DECENTRALIZED PRIVACY IN IOT HEALTHCAREIJCI JOURNAL
With the advent of the Internet of Things (IoT), e-health has become one of the main topics of research. Due to the sensitivity of patient information, patient privacy seems challenging. Nowadays, patient data is usually stored in the cloud in healthcare programs, making it difficult for users to have enough control over their data. The recent increment in announced cases of security and surveillance breaches compromising patients' privacy call into question the conventional model, in which third-parties gather and control immense amounts of patients' Healthcare data. In this work, we try to resolve the issues mentioned above by using blockchain technology. We propose a blockchain-based protocol suitable for ehealth applications that does not require trust in a third party and provides an efficient privacy-preserving access control mechanism. Transactions in our proposed system, unlike Bitcoin, are not entirely financial, and we do not use conventional methods for consensus operations in blockchain like Proof of Work (PoW). It is not suitable for IoT applications because IoT devices have resources-constraints. Usage of appropriate consensus method helps us to increase network security and efficiency, as well as reducing network cost, i.e., bandwidth and processor usage. Finally, we provide security and privacy analysis of our proposed protocol.
This document proposes an e-health cloud solution to securely store patient health records and reports in the cloud. Previously, patient documents were stored physically taking up space and making it difficult to access old records. The cloud solution aims to address these issues by digitizing records and storing them securely in the cloud. This allows easy access to records from anywhere and saves space. The document discusses challenges with healthcare cloud computing like data security and privacy. It proposes using encryption and multi-factor authentication for cloud data and user access security.
IRJET- Implementation of Cloudlet-based Medical Data Sharing using ECC Crypto...IRJET Journal
This document proposes a cloudlet-based medical data sharing framework that uses encryption to securely share patient data. It discusses encrypting medical data with ECC cryptography before storing it on a cloudlet. A collaborative intrusion detection system is also developed to protect the remote healthcare cloud from attacks. The framework allows trusted partners like doctors to access encrypted data from the cloudlet after being authenticated. It aims to securely share medical data for similar patients while preserving patient privacy.
Cloud assisted privacy preserving and data integrity for mobile health monito...eSAT Journals
Abstract
In cloud computing system ,data is stimulated to a distantly placed cloud server. Cloud provisions the information authentically and go back to the proprietor whenever wanted. But there is no assurance that information store in the cloud is protected and not changed by cloud . In order to defeat the danger of honesty of data, the user must be able to use the help of Third party Auditor(TPA).TPA has understanding in inspection honesty of the information, that clouds users does not have, and that is difficult for the owner to check .The data in the cloud should be exact ,reliable ,available and elevated excellence.[1]This paper is to address this important problem related to the data integrity and design a cloud assisted privacy preserving mobile-health monitoring system to protect the privacy of the involved parties and their data. for that purpose we have used the algorithms:1)Tate pairing 2)Token generation 3)AES(Advanced Encryption Standards)-SHA1 and MD5.
Keywords— Data integrity,TPA,Tate pairing, Cryptography
Achieving Data Dissemination with Security using FIWARE and Intel Software Gu...Dalton Valadares
This document proposes and evaluates a solution to securely disseminate sensitive IoT data using FIWARE and Intel SGX. The solution uses FIWARE components for authentication and authorization, and introduces a new Key Vault component that uses Intel SGX to securely store and manage encryption keys. Sensitive IoT data from smart meters is encrypted before being sent to the FIWARE Orion Context Broker for processing. Consumers that are SGX applications can decrypt and process the data securely within the SGX enclave. The evaluation shows the solution provides privacy and security guarantees without harming scalability or availability.
Security and Privacy of Big Data in Mobile DevicesIOSRjournaljce
Presently, the volume of data generated via mobile devices is at an exponential rate due to the rapid advancement in internet-enabled mobile devices, which makes it complex to ensure the privacy and security of this data. Cloud-based server is currently considered one of the most reliable solutions to address these issues. Nevertheless, the increasing uncertainties of storing useful and sensitive big data in a public cloud have suppressed the exploration of this option. In our paper, we meticulously reviewed the drawbacks in the current adopted solutions for security and privacy of big data within mobile devices. As the utilization of mobile platforms is increasingly generating large data, the current traditional methods of cryptography will not be able to efficiently ensure the security and privacy of this big data. Therefore, this paper will propose the utilization of Federated Identity Management that is Openstack cloud-based as an effective solution that can ensure the privacy and security of big data within mobile device ecosystem.
IRJET- Secure Re-Encrypted PHR Shared to Users Efficiently in Cloud ComputingIRJET Journal
This document proposes a Securely Re-Encrypted PHR Shared to Users Efficiently in Cloud Computing (SeSPHR) system. The SeSPHR system aims to securely store and share patients' Personal Health Records (PHRs) with authorized entities in the cloud while preserving privacy. It encrypts PHRs stored on untrusted cloud servers and only allows verified users access using re-encryption keys from a semi-trusted proxy server. The system enforces patient-centric access management of PHR components based on access levels and supports dynamic addition and removal of authorized users. The operation of SeSPHR was analyzed and verified using High-Level Petri Nets, SMT-Lib and Z3 solver. Performance analysis
This document discusses strategies for ensuring the security of enterprise image viewers and mobile health solutions. It notes that data security is a major concern in healthcare, with security breaches potentially resulting in large fines. The document then recommends educating staff on mobile security, using device security features, implementing network security policies, using authentication, secure connections, and ensuring solutions have built-in encryption and integrate with IT policies. It outlines Calgary Scientific's approach to securing its ResolutionMD image viewer, which does not leave patient data on devices, requires login credentials, uses SSL encryption, and optionally a VPN.
Framework to Manage Big Data in Smart Home Servicesijtsrd
In order to improve the effect of smart home control and management, a new smart home control and management method based on big data analysis is designed. The basic hardware of smart home control and management is designed, including smoke sensor hardware, temperature and humidity sensor hardware, and infrared sensor hardware, so as to collect smart home data and realize data visualization and buzzer alarm. The collected data are transmitted through the indoor wireless network of smart home gateway equipment, and the data distributed cache architecture based on big data analysis is used to store smart home data. Based on the relevant data, the hybrid particle swarm optimization algorithm is used to schedule the control and management tasks of smart home to complete the control and management of smart home. Dr. Rajendra Kumar Bharti "Framework to Manage Big Data in Smart Home Services" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd52102.pdf Paper URL: https://www.ijtsrd.com/computer-science/other/52102/framework-to-manage-big-data-in-smart-home-services/dr-rajendra-kumar-bharti
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document discusses privacy issues in cloud computing. It defines privacy and describes privacy enhancing technologies (PETs) that can help protect privacy, such as pseudonymization and federated identity management. It also discusses privacy by design, which aims to embed privacy protections directly into technologies. Ensuring privacy in cloud computing requires measures like access controls, protecting against unauthorized access/copying of data, and specifying privacy controls in agreements. Overall privacy is a major challenge for cloud computing due to issues of data governance, security, and differing international regulations.
IRJET - Health Record Transaction in Hospital Management using BlockchainIRJET Journal
This document proposes a Secure and Efficient Health Record Transaction algorithm (SEHRTB) using blockchain technology. The SEHRTB aims to securely store and transact health records between patients, doctors, hospitals, and insurance agents in a decentralized manner. It describes a system where patient health records are encrypted and stored on a distributed ledger. Only authorized parties like doctors and insurance agents can access the encrypted records after getting the necessary keys. The proposed SEHRTB algorithm is evaluated and shown to reduce latency, execution time, and improve throughput compared to existing methods. The system aims to provide privacy and security for health records transactions using blockchain.
The document discusses encryption strategies used by organizations that have experienced data breaches. While encryption is commonly used, it is often not applied or used properly, leaving entire systems vulnerable. For encryption to be effective, companies must use a comprehensive defense in depth strategy where data is encrypted and keys are protected across all systems where encrypted data needs to be accessed and managed. Target spent heavily on security but a weakness allowed cybercriminals to access encrypted data in memory before it was encrypted. Stronger defenses are needed at each layer to block attacks.
Enhancing security features in cloud computing for healthcare using cipher an...eSAT Journals
Abstract Health Care is the most important unindustrialized field. Cloud is an emerging trend in software industry. In medical field, there are large dataset comprising highly sensitive data about patient’s medical records. Based on these records, diagnosis for the patient will be given. Moving data to the cloud makes to explore a large information for diagnosis as expert documentation will also be stored as part of health record. Physicians from anywhere at any time can get access over these reports for better treatment. The Medicare industry vacillates to store these data to the cloud as the patients might feel insecure about their health records. This work introduces the idea of combining Cipher Cloud, Inter Cloud and ABE schemes, proposes an innovative method to enhance security features in the cloud by double encryption using algorithms and tools. By this, only authorized entities are proficient of accessing these records. Rather than storing data in single cloud, Inter Cloud (Multi-cloud) also adds advantage for our proposed work. Keywords: Virtualization, Cipher cloud, Trust, Encryption, Inter cloud
Enhancing security features in cloud computing for healthcare using cipher an...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
I want you to Read intensively papers and give me a summary for ever.pdfamitkhanna2070
I want you to Read intensively papers and give me a summary for every paper and the linghth for
each paper is 2 pages or more. In the summary, you need to provide some of your own ideas.
Research Interests: Privacy-Aware Computing,Wireless and Mobile Security,Fog
Computing,Mobile Health and Safety, Cognitive Radio Networking,Algorithm Design and
Analysis.
You should select papers from the following conferences:
IEEE INFOCOM, IEEE Symposium on security and privacy, ACM CCS, USENIX Security.
Solution
PRIVACY AWARE COMPUTING
Introduction
With the increasing public concerns of security and personal data privacy worldwide, security
and privacy become an important research area. This research area is very broad and covers
many application domains.
The security and privacy aware computing research group actually focuses on
(1) privacy-preserved computing,
(2) Video surveillance, and
(3) secure biometric system.
Now let us briefly discuss the above three groups.
Privacy-preserved Computing
Concerns on the data privacy have been increasing worldwide. For example, Apple was
reportedly fined by South Korea’s telecommunications regulator for allegedly collecting and
storing private location data of iPhone users. The privacy concerns raised by both end-users and
government authorities have been hindering the deployment of many valuable IT services, such
as data mining and analysis, data outsourcing, and mobile location-aware computing.
soo, in response to the growing necessity of protecting data privacy, our research group has been
focusing on developing innovative solutions towards information services --- to support these
services while preserving users’ personal privacy.
Video Surveillance
With the growing installation of surveillance video cameras in both private and public areas, the
closed-circuit TV (CCTV) has been evolved from a single camera system to a multiple camera
system; and has recently been extended to a large-scale network of cameras.
One of the objectives of a camera network is to monitor and understand security issues in the
area under surveillance. While the camera network hardware is generally well-designed and
roundly installed, the development of intelligent video analysis software lags far behind. As
such, our group has been focusing on developing video surveillance algorithms such as face
tracking, person re-identification, human action recognition.
Our goal is to develop an intelligent video surveillance system.
Secure Biometric System
With the growing use of biometrics, there is a rising concern about the security and privacy of
the biometric data. Recent studies show that simple attacks on a biometric system, such as hill
climbing, are able to recover the raw biometric data from stolen biometric template. Moreover,
the attacker may be able to make use of the stolen face template to access the system or cross-
match across databases. Our group has been working on face template protection, multimodality
template protection, and .
Healthcare information exchange using blockchain technologyIJECEIAES
This document proposes a blockchain-based healthcare information exchange system using Hyperledger Fabric. The system would allow secure sharing of electronic health records between patients, doctors, hospitals, insurance companies, and research organizations. Medical data is sensitive, so a permissioned blockchain like Hyperledger Fabric is used to control access while maintaining privacy. The system aims to provide consistent and accessible health records for patients while giving them control over access permissions. A backup access system using wearable devices would allow access to critical health information in emergencies.
Similar to Cloud-Native Security on Digital Health-Telehealth Use Case (20)
1. What Is “Metaverse”?
2. Use Cases of Metaverse in Healthcare: Robot-Assisted Surgery (RAS) Systems
3. What Is “Web3/NFTs”?
4. Use Cases of Web3/NFTs in Healthcare: Secure Health Information Exchange
5. Conclusion/Q&A
1. 米国立標準技術研究所(NIST) NIST SP 1800-30 遠隔医療の遠隔患者モニタリングエコシステムのセキュア化」草案第2版(2021年5月6日発行)
2. CSA Health Information Management WG 「クラウド上の遠隔医療データ」(2020年6月16日発行)
3. CSA Health Information Management WG 「遠隔医療のリスク管理」(2021年8月10日発行)
4. Q&A/ディスカッション
1. Use Case: Robot-Assisted Surgery (RAS) System on the Cloud
2. Worldwide IT Industry 2023 Predictions
3. Japan IT Spending Forecast by Region: 2021-2026
4. Japan Public Cloud Spending Forecast: 2021-2026
5. Japan Private Cloud Spending Forecast: 2021-2026
6. Japan Information Security Market Forecast: 2020-2026
7. Green Transformation (GX) in Healthcare
8. Conclusion/Q&A
1. 米国の次世代創薬基盤技術開発における官民連携パートナーシップの取組事例
2. CSA Health Information Management WG「クラウドにおける医療ビッグデータ」 (2020年7月21日発行)
3. CSA Health Information Management WG「クラウドにおける医療データのプライバシー保護」(2021年8月10日発行)
4. Q&A/ディスカッション
Skybuffer AI: Advanced Conversational and Generative AI Solution on SAP Busin...Tatiana Kojar
Skybuffer AI, built on the robust SAP Business Technology Platform (SAP BTP), is the latest and most advanced version of our AI development, reaffirming our commitment to delivering top-tier AI solutions. Skybuffer AI harnesses all the innovative capabilities of the SAP BTP in the AI domain, from Conversational AI to cutting-edge Generative AI and Retrieval-Augmented Generation (RAG). It also helps SAP customers safeguard their investments into SAP Conversational AI and ensure a seamless, one-click transition to SAP Business AI.
With Skybuffer AI, various AI models can be integrated into a single communication channel such as Microsoft Teams. This integration empowers business users with insights drawn from SAP backend systems, enterprise documents, and the expansive knowledge of Generative AI. And the best part of it is that it is all managed through our intuitive no-code Action Server interface, requiring no extensive coding knowledge and making the advanced AI accessible to more users.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3Data Hops
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
A Comprehensive Guide to DeFi Development Services in 2024Intelisync
DeFi represents a paradigm shift in the financial industry. Instead of relying on traditional, centralized institutions like banks, DeFi leverages blockchain technology to create a decentralized network of financial services. This means that financial transactions can occur directly between parties, without intermediaries, using smart contracts on platforms like Ethereum.
In 2024, we are witnessing an explosion of new DeFi projects and protocols, each pushing the boundaries of what’s possible in finance.
In summary, DeFi in 2024 is not just a trend; it’s a revolution that democratizes finance, enhances security and transparency, and fosters continuous innovation. As we proceed through this presentation, we'll explore the various components and services of DeFi in detail, shedding light on how they are transforming the financial landscape.
At Intelisync, we specialize in providing comprehensive DeFi development services tailored to meet the unique needs of our clients. From smart contract development to dApp creation and security audits, we ensure that your DeFi project is built with innovation, security, and scalability in mind. Trust Intelisync to guide you through the intricate landscape of decentralized finance and unlock the full potential of blockchain technology.
Ready to take your DeFi project to the next level? Partner with Intelisync for expert DeFi development services today!
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Programming Foundation Models with DSPy - Meetup Slides
Cloud-Native Security on Digital Health-Telehealth Use Case
1. Cloud-Native Security on Digital Health
-Telehealth Use Case-
GVHS 2022 on December 9, 2022
EIJI SASAHARA, PH.D., MBA
HEALTHCARE CLOUD INITIATIVE, NPO
CLOUD SECURITY ALLIANCE
HEALTH INFORMATION MANAGEMENT WG
2. AGENDA
1. Cybersecurity on Telehealth @NIST
2. Cybersecurity on Telehealth x Smart Home
@NIST
3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA
4. Cloud-Native Security on Telehealth @CSA
5. Conclusions
2
https://www.linkedin.com/in/esasahara
https://www.facebook.com/esasahara
https://twitter.com/esasahara
3. 1. Cybersecurity on Telehealth @NIST (1)
“NIST SP1800-30 Securing Telehealth Remote Patient
Monitoring Ecosystem”, February 22, 2022
https://csrc.nist.gov/publications/detail/sp/1800-30/final
SP 1800-30A: Executive Summary
SP 1800-30B: Approach, Architecture, and Security
Characteristics
1. Summary
2. How to Use This Guide
3. Approach
4. Architecture
5. Security and Privacy Characteristic Analysis
6. Functional Evaluation
7. Future Build Considerations
SP 1800-30C: How-To Guides
3
Source:”NIST SP 1800-30: Securing Telehealth
Remote Patient Monitoring Ecosystem, February
22, 2022
8. 2. Cybersecurity on Telehealth x Smart Home
@NIST (1)
NIST “Mitigating Cybersecurity Risk in Telehealth Smart Home
Integration: Cybersecurity for the Healthcare Sector”,
August 29, 2022
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-
integration/final
Objective: identify and mitigate cybersecurity and privacy risks based on
patient use of smart home devices interfacing with patient information
systems
a practice guide that describes a reference architecture for smart
home integration with healthcare systems as part of a telehealth
program.
Reference:
“NIST IR 8259: Foundational Cybersecurity Activities for IoT Device Manufacturers”, May 29, 2020
https://www.nist.gov/publications/foundational-cybersecurity-activities-iot-device-manufacturers
“NIST IR 8259A: IoT Device Cybersecurity Capability Core Baseline”, May 29, 2020
https://www.nist.gov/publications/iot-device-cybersecurity-capability-core-baseline
“NIST IR 8259B:IoT Non-Technical Supporting Capability Core Baseline”, August 25, 2021
https://csrc.nist.gov/publications/detail/nistir/8259b/final
8
9. 2. Cybersecurity on Telehealth x Smart Home
@NIST (2)
Components of Architecture
9
Architecture Components
Patient Home Environment Smart Home Devices, Personal Firewall, Wireless
Access Point Router, Internet Router
Cloud Service Provider
Environment
Voice Assist Platform, Cloud Platform
Healthcare Technology
Integration Solution
Environment
Telehealth Integration Applications
Health Delivery Organization
(HDO) Environment
Electronic Health Record (EHR) System, Patient Portal,
Network Access Control, Network Firewall, VPN
Telehealth Ecosystem Actors Patients, HDO Clinicians, Support/Maintenance Staff
10. 2. Cybersecurity on Telehealth x Smart Home
@NIST (3)
High-Level Architecture
10
Source:National Institute of Standards and Technology (NIST), “Project Description] Mitigating Cybersecurity Risk in Telehealth Smart
Home Integration: Cybersecurity for the Healthcare Sector”(August 29, 2022)
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-integration/final
11. 2. Cybersecurity on Telehealth x Smart Home
@NIST (4)
Scenario 1: Patient Visit Scheduling
11
Source:National Institute of Standards and Technology (NIST), “Project Description] Mitigating Cybersecurity Risk in Telehealth Smart
Home Integration: Cybersecurity for the Healthcare Sector”(August 29, 2022)
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-integration/final
12. 2. Cybersecurity on Telehealth x Smart Home
@NIST (5)
Scenario 2: Patient Prescription Refill
12
Source:National Institute of Standards and Technology (NIST), “Project Description] Mitigating Cybersecurity Risk in Telehealth Smart
Home Integration: Cybersecurity for the Healthcare Sector”(August 29, 2022)
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-integration/final
13. 2. Cybersecurity on Telehealth x Smart Home
@NIST (6)
Scenario 3: Patient Regimen Check-In
13
Source:National Institute of Standards and Technology (NIST), “Project Description] Mitigating Cybersecurity Risk in Telehealth Smart
Home Integration: Cybersecurity for the Healthcare Sector”(August 29, 2022)
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-integration/final
14. 2. Cybersecurity on Telehealth x Smart Home
@NIST (7)
Security Control Map: NIST SP 800-53 Revision 5
•IEC TR 80001-2-2
•HIPAA Security Rule
•ISO/IEC 27001
14
Source:National Institute of Standards and Technology (NIST), “Project Description] Mitigating Cybersecurity Risk in Telehealth Smart
Home Integration: Cybersecurity for the Healthcare Sector”(August 29, 2022)
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-integration/final
15. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(1)
Cloud Security Alliance Health Information Management WG,
“Telehealth Data in the Cloud”, June 16, 2020
https://cloudsecurityalliance.org/artifacts/telehealth-data-in-the-cloud/
[Contents]
Introduction
Privacy Concerns
Security Concerns
Governance
Compliance
Confidentiality
Integrity
Availability
Incident Response and Management
Maintaining a Continuous Monitoring Program
Conclusion
References
15
Source:CSA Health Information Management
WG, “Telehealth Data in the Cloud”, June 16,
2020
16. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(2)
Considerations for Health Delivery Organizations
(HDOs) regarding a Telehealth Agreement with a
Cloud Provider:
16
# Key Questions
1 Does the telehealth provider (TP) describe the purpose(s) for which PHI is collected, used,
maintained, and shared in its privacy notices?
2 Does the TP have, disseminate, and implement operational privacy policies and procedures
that govern the appropriate privacy and security controls for programs, information systems,
or technologies involving PHI?
3 Has the TP conducted a privacy impact assessment, and are they willing to share it?
4 Does the HDO have privacy roles, responsibilities, and access requirements for contractors
and service providers?
5 Does the TP monitor and audit privacy controls and internal privacy policies to ensure
effective implementation?
6 Does the TP design information systems to support privacy by automating privacy controls?
17. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(3)
(Continue)
17
# Key Questions
7 Does the TP maintain an accurate accounting of disclosures of information held in each system
of records under its control, including:
a. Date, nature, and purpose of each disclosure of a record.
b. Name and address of the person or organization to which the disclosure was made.
c. The identity of who authorized the disclosure.
8 Does the TP document processes to ensure the integrity of PHI through existing security
controls?
9 Does the TP identify the minimum PHI elements relevant and necessary to accomplish the legally
authorized purpose of collection?
10 Does the TP provide means for individuals to authorize the collection, use, maintenance, and
sharing of PHI before its collection?
11 Does the TP have a process for receiving and responding to complaints, concerns, or questions
from individuals about organizational privacy practices?
12 Does the TP provide sufficient notice to the public and to individuals regarding its activities that
impact privacy? (e.g. collection, use, sharing, safeguarding, maintenance, and disposal of PHI)
13 Does the TP share PHI externally?
18. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(4)
Governance
Compliance
18
# Key Questions
1 Does the service provider’s service-level agreement (SLA) clearly define how the service
provider protects the confidentiality, integrity, and availability of all customer information?
2 Does the service provider’s SLA specify that the HDO will retain ownership of its data?
3 Will the service provider use the data for any purpose other than service delivery?
4 Is the service provider’s service dependent on any third-party stakeholders?
# Key Questions
1 Does the cloud service provider allow the HDO to directly audit the implementation and
management of the security measures in place to protect the service and the data it holds?
2 Will the service provider allow the HDO to review recent audit reports thoroughly?
3 Is the service provider HIPAA compliant?
4 Does the service provider comply with the GDPR?
19. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(5)
Confidentiality
Protecting data from improper disclosure
19
# Key Questions
1 Authentication and Access Control
a. Does the HDO have an identity management strategy that supports the adoption of cloud
services?
b. Is there an effective internal process that ensures that identities are managed and protected
throughout their lifecycles?
c. Is there an effective audit process to ensure that user accounts are appropriately managed
and protected? Does the service provider meet those control requirements?
d. Are all passwords encrypted, especially system/service administrators?
e. Is multi-factor authentication required, and, if so, is it available?
f. Does authentication and access control extend to devices?
2 Multi-Tenancy
g. Will the service provider allow the HDO to review a recent third-party audit report that
includes an assessment of the security controls and practices related to virtualization and
separation of customer data?
h. Do the service provider’s customer registration processes provide an appropriate level of
assurance based on the criticality and sensitivity of the information in the cloud service?
20. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(6)
(Continue)
20
# Key Questions
3 Patch and Vulnerability Management
i. Is the service provider responsible for patching all components that make up the cloud
service?
j. Does the service provider’s SLA include service levels for patch and vulnerability
management that comprise a defined maximum exposure window?
k. Does the HDO currently have an effective patch and vulnerability management process?
l. Will the service provider allow the HDO to perform regular vulnerability assessments?
4 Encryption
m. Does the service provider encrypt the information placed in the cloud service for both data
at rest and in transit?
n. Does the cloud service use only approved encryption protocols and algorithms (as defined in
Federal Information Processing Standards 140-2)?
o. Which party is responsible for managing the cryptographic keys?
p. Are there separate keys for each customer?
5 Data Persistence
q. Does the service provider have an auditable process for the secure sanitization of storage
media before it is made available to another customer?
r. Does the service provider have an auditable process for safe disposal or destruction of
equipment and storage media containing customer data?
21. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(7)
Integrity
Maintenance of data over its full lifecycle with the assurance it is
accurate and consistent.
consistent.
21
# Key Questions
1 Does the service provider provide data backup or archiving services as part of their standard
service offering to protect against data loss or corruption?
2 How are data backup and archiving services provided?
3 Does the data backup or archiving service adhere to business requirements related to protection
against data loss?
4 What level of granularity does the service provider offer for data restoration?
5 Does the service provider regularly perform test restores to ensure that data is recoverable from
backup media?
22. 3. Cloud-Native Privacy/Data Protection
on Telehealth @CSA(8)
Availability
Ability to ensure that required data is always accessible when and where needed.
22
# Key Questions
1 Does the SLA include an expected and minimum availability performance percentage over a clearly
defined period?
2 Does the SLA include defined, scheduled outage windows?
3 Does the service provider utilize protocols and technologies that can protect against distributed
denial-of-service (DDoS) attacks?
4 Do the network services directly managed or subscribed to by the HDO provide sufficient levels of
availability?
5 Do the network services directly managed, or subscribed to by the HDO provide an adequate level
of redundancy/fault tolerance?
6 Do the network services directly managed, or subscribed to by the HDO provide an adequate level
of bandwidth?
7 Is the latency between the HDO network(s) and the service provider’s service at levels acceptable
to achieve the desired user experience?
23. 4. Cloud-Native Security on Telehealth @CSA(1)
Cloud Security Alliance Health Information Management WG,
“Telehealth Data in the Cloud”, June 10, 2021
https://csrc.nist.gov/publications/detail/white-paper/2022/08/29/mitigating-cyber-risk-in-telehealth-smart-home-
integration/final
[Contents]
Introduction
Governance
Privacy
Security
Conclusion
Reference
23
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
24. 4. Cloud-Native Security on Telehealth @CSA(2)
Information Governance:
Establish the system,
strategy, policies,
procedures, guidelines,
laws, and regulations
that HDOs must adhere
to.
24
Source:CSA Health
Information Management WG,
“Telehealth Risk management”,
June 10, 2021
25. 4. Cloud-Native Security on Telehealth @CSA(3)
Data Lifecycle:
25
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
Phase Definition
1. Create: Data is generated, acquired, or modified.
2. Store: Data is committed to a storage repository.
3. Use: Data is processed, viewed, or used in any other sort of
activity.
4. Share: Data or information is made accessible to others.
5. Archive: Data is placed in long-term storage, per data retention
guidelines and legal obligations.
6. Destroy: Data is no longer required and made inaccessible.
26. 4. Cloud-Native Security on Telehealth @CSA(4)
Cybersecurity and Pivacy Risk Relationship
26
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
27. 4. Cloud-Native Security on Telehealth @CSA(5)
Data Lifecycle and Cybersecurity(1)
27
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
Phase Considerations
1. Create: ・Any created data should fulfill a clear business need.
・HDOs must have consent to collect PHI or PII.
・Data creation regulatory requirements depend on where data is created.
・GDPR requires security be built in at the time of data creation.
・HIPAA requires protection for all PHI from inception to destruction.
・Data must be created in a secure environment.
2. Store: ・Data owners must determine where data originated and where it is
stored.
・Service providers must protect cloud data (including access control
and encryption).
・CSP should have a secure architecture that utilizes standard security
best practices. (e.g. robust monitoring, auditing, and alerting capability)
・Data loss prevention system can help identify who is using the data
and their location.
・CSP should complete a third party assessment and offer to share that
insight with the HDO.
28. 4. Cloud-Native Security on Telehealth @CSA(6)
Data Lifecycle and Cybersecurity(2)
28
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
Phase Considerations
3. Use: ・Geography determines the regulatory requirements for both stored and
processed data. (e.g. Telehealth solutions allow patients to access data from
anywhere with internet access.)
Organizations should use federation and multifactor authentication whenever
possible access data.
・Identity and Access Management (IAM) is a vital part of securing data in use.
・Organizations should consider using an Application Programming Interface
(API), which requires digital signatures to ensure security.
4. Share: ・When data sharing is required, the organization responsible for the data
must ensure its security. IAM is critical for data security.
・Enact a Data Loss Prevention (DLP) program to discover, monitor, and
protect data with regulatory or compliance implications in transit and at rest
across the network, storage, and endpoints.
Sharing requires data transmission from the cloud to all applicable data users.
・Encrypt data while in transit and use a secure protocol.
29. 4. Cloud-Native Security on Telehealth @CSA(7)
Data Lifecycle and Cybersecurity(3)
29
Source:CSA Health Information Management WG, “Telehealth Risk management”, June 10, 2021
Phase Considerations
5. Archive: ・Essential data that does not require frequent access or modification
often resides in a data archive.
・Archiving data provides many benefits, especially in terms of efficiency.
・Encrypt archived data and control access to the information.
・Keep personal data or healthcare data only if required for its original,
intended purpose.
6. Destroy: ・Since cloud data exists in a shared, dispersed environment, typical
data deletion and destruction methods (such as wiping) cannot ensure
all data copies are destroyed.
・Encryption, followed by key destruction, is the best guarantee to
ensure responsible data removal.
30. 5. Conclusions
1. Adoption of NIST Cybersecurity Framework in
Emerging Telehealth Services
2. Next Challenge: Integration of Telehealth with
Smart Home
3. Privacy/Data Protection by Design:
Agreement with Cloud Telehealth Providers
4. Cloud-Native Security with Continuous
Data Lifecycle Management
30